Dimensioning systems are useful for providing dimensional and volumetric data related to three-dimensional objects disposed within a field-of-view of the dimensioning system. Such dimensional and volumetric information is useful for example, in providing consumers with accurate shipping rates based on the actual size and volume of the object being shipped. Additionally, the dimensioning system's ability to transmit parcel data immediately to a carrier can assist the carrier in selecting and scheduling appropriately sized vehicles based on measured cargo volume and dimensions. Finally, the ready availability of dimensional and volumetric information for all the objects within a carrier's network assists the carrier in ensuring optimal use of available space in the many different vehicles, containers, and/or warehouses used in local, interstate, and international commerce.
A wide variety of computing devices are used within the shipping industry. For example, personal computers used as multi-tasking terminals in small storefront packing and shipping establishments. Also, for example, dedicated self-service shipping kiosks found in many post offices. As a further example, dedicated handheld scanners are frequently used as mobile terminals by many international shipping corporations. The wide variety of form factors found in the shipping industry are quite diverse, yet all rely upon providing accurate information, such as parcel dimensions and volume, to both the user in order to provide accurate shipping rates and to the carrier in order to accurately forecast shipping volumes.
A number of volume dimensioning systems rely upon the use of structured light. By projecting a structured light pattern into a three-dimensional space containing at least one object, the shift in position (i.e., parallax) of the structured light within the three-dimensional space may be used to determine one or more dimensions of the object. The comparison between the structured light pattern present in the acquired image containing the object and a reference image to determine the parallax shift and consequently the volume dimensions of the object is performed graphically, often by comparing portions of the acquired image to portions of the entire reference image to determine a pattern “match.” Such image intensive processing requires significant computing resources and speed to provide response times expected for use in commerce and industry.
Structured light patterns can take many forms, including an outwardly apparent random pattern of elements (e.g., visible or invisible electromagnetic radiation in the form of “dots” or “spots”) which is, to the contrary, highly structured. The arrangement of elements within the pattern is such that any group including a defined number of elements (e.g., three or more) is unique among all other groups containing an identical number of elements within in the pattern. Thus in some element patterns, any group of seven elements is unique among all groups of seven elements appearing in the pattern.
Projecting such a pattern of elements into a three-dimensional space that includes an object for volume dimensioning permits the determination of the volume dimension of the object based on the parallax shift that occurs in at least a portion of the elements in the pattern when the acquired image data is compared to reference data of the three-dimensional space without the object. Determination of parallax shift between the acquired image of the three-dimensional space with an object and containing the pattern of elements and a reference image containing the pattern of elements is a two step process in which corresponding elements in the acquired image and the reference image are identified. After corresponding elements in the reference image and the acquired image are identified, the parallax shift between the elements can be calculated, and dimensional information of the object obtained.
The identification of corresponding elements in the reference image and the acquired image may be performed graphically using a processor-based device to sequentially compare a portion of the acquired image with portions of the reference image until a “match” between the patterns is detected by the processor. Such graphical comparisons are generally computationally intensive, requiring the use of either high speed processors or multiple processors to reduce the time required to match the pattern in the acquired image with the pattern in the reference image to a level acceptable for use in industry and commerce.